Searching a compromise between ecological quality targets ... · River restoration of the instream...

1

Searching a compromise between ecological quality targets, social and

ecosystem costs for Heavily Modified Water Bodies (HMWBs): the

Lambro-Seveso-Olona system case study

Arianna Azzellino

2 BACKGROUND

Changes in the UE (Water Framework Directive 2000/60CE), and national legislation which moved toward a watershed-based approach.

Environmental Quality Standard criterion versus the previous concept of the Standard Limit

Need to consider the changes of polluting loads (either point or non point sources) along the stream networks.

Need for developing decision-support tools on the field of the resource planning

C mg/l

Cb

Criteria/standard

Impaired reach

P1 P2 P3

2

3

KEY ISSUES ADDRESSED

Which is the effect for the whole watershed of a restoration strategy?

What are the most significant pollution sources?

When the full restoration cannot be achieved, how it could be defined an alternative restoration goal?

How to select among competitive restoration strategies?

4


Which is the effect for the whole watershed of a restoration strategy?

Not simulated

Class I Class II

Class III

Quality Classification

Monitoring stations Industrial discharges

Urban WWT plants Hydrography

County boundaries

3

5 Restoration Strategy Scenario

Plant Efficiency Upgrade: What will be the effect on the river of the upgrade of these WWT plants?

6 Model Structure

For every computational unit the mass balance of input and output flows and pollutants is considered

Qual2K Computational unit

A

Timbro

4

7 Restoration Scenario

BOD5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

VALD

IDENTR

O

SONDALO

VIL

LA D

I TIR

ANO

CAIO

LO

ARDENNO

GERA L

ARIO

km

mg

/l

ottimo buono

Serie4Scenario medio annuo

N-NH4

0

0.02

0.04

0.06

0.08

0.1

0.12

VALD

IDENTR

O

SONDALO

VIL

LA D

I TIR

ANO

CAIO

LO

ARDENNO

GERA L

ARIO

km

mg

/l

ottimo

buono


N-NO3

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

VALD

IDENTR

O

SONDALO

VIL

LA D

I TIR

ANO

CAIO

LO

ARDENNO

GERA L

ARIO

km

mg

/l

ottimo buono


P tot

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

VALD

IDENTR

O

SO

NDALO

VIL

LA D

I TIR

ANO

CAIO

LOARDENNO

GERA L

ARIO

km

mg

/l

ottimo

buono


Class I Class II

Restoration Scenario

Class I Class II

Restoration Scenario

Class I Class II Restoration Scenario

Class I Class II Restoration Scenario

Improvement Improvement

Improvement Improvement

8


When the full restoration cannot be achieved, how it could be defined an alternative restoration goal?

How to select among competitive restoration strategies?

5

9 Study Area

Lombardy

Although representing only 6% of Po river

drainage area, the contribution of in terms

of pollutant load is significant and has

been largely documented in literature.

The Lambro-Seveso-Olona system is

part of the Po river district and it

constitutes the most polluted tributary

of the Po river.

10 The Lambro-Seveso-Olona system

Watershed of 2700 Km2,

Population Density: Average: 1600 Inhab./Km2; Max: 7000 Inhab./Km2 (Milan); among the highest in Italy and Europe

Industrial district: chemical, textile, paper, pulp and food industries

Half of the streamflow constituted by WWTP effluents

6

11 The “Urban Stream Syndrome”

Walsh et al., 2005

1 3

2

Synergistic action of multiple stressors

(among others…)

1. Different kinds of pollution

2. Increased hydraulic flashiness

3. Habitat destruction

Limits to the development of Biological Communities

12 The Lambro-Seveso-Olona system

7

13 The LIMeco Index

New quality standards for macropollutants have recently been set by the Italian

legislation as support for the good ecological status (i.e. LIMeco index according

the legislative decree n.152, 2006).

The achievement of water quality objectives according to the LIMeco index are

challenging for many Italian rivers. In a previous study It has been shown that

the Lambro-Seveso-Olona will never comply with these LIMeco standards.

Thresholds

LIMeco high good moderate poor bad LIMeco

100-DOsat 0 0 0 0 > 80 high 0.66

N-NH4 (mg/l) < 0.03 6 0. 2 0.24 > 0.24 good 0.5

N-NO3 (mg/l) < 0.6 1.2 .4 .8 > 4.8 moderate 0.33

Total-P (ug/l) < 50 200 200 400 > 400 poor 0.17

bad < 0.17

Score 1 0.5 0.25 0.125 0

14 Aims of the study and Scenario Analysis

To evaluate the restoration possibilities of L-S-O

1. To provide appropriate indexes of Effectiveness

2. To evaluate restoration scenarios through a Cost-Effectiveness

approach

LIMeco classification

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sc 2009 Sc Dir 271/91 Sc MBR Sc RO

% o

f ri

ver

len

gth

bad

poor

good

high

Azzellino et al. 2013, Water Science and Techonology

8

15 Methods

• The QUAL2K model (Chapra et al., 2008) was employed in the Scenario

Analysis

• Measurements of different water quality parameters at 44 sampling

monitoring sites (source: ARPA Lombardia) were used to implement the

water quality simulations.

The QUAL2K model showed overall a

discrete model accuracy (i.e. errors of about

± 20-30%) for the median annual scenario.

The median was assumed as reference for

the scenarios and it was preferred to the

average to avoid any skewness effect

present in the water quality measurements.

16

Restoration Scenarios

• Five simulated scenarios:

1. Dir 271/91 the upgrading of the existing WWTPs up to the requirements of the

Directive 271/91EC;

2. MBR the full replacement of the actual technology with a secondary

membrane treatment stage (MBR) in all the existing WWTPs larger than 50,000

PE.

3. RO the upgrade of the actual technology with a tertiary Reverse Osmosis

treatment (RO) operating at a 50/50 blend in all the existing WWTPs larger than

50,000 PE.

4. PostDen the upgrade of the conventional activated sludge treatment scheme

with an additional post-denitrification treatment in all the existing WWTPs larger

than 50,000 PE.

5. O3/GAC the upgrade of the conventional activated sludge treatment scheme

with a ozonation treatment with a subsequent granular activated carbon (GAC)

filtration in all the existing WWTPs larger than 50,000 PE

9

17 Restoration Scenarios: model assumptions

Effluent concentrations assumed in the wastewater treatment plants as

function of the plant size (expressed as People Equivalent, PE) in the

considered scenarios.

mg/l Dir 271/91CE MBR RO PostDen GAC/O3

PE

<100,000

PE

>100,000

PE

>50,000

PE

>50,000

PE

>50,000

PE

<100,000

PE

>100,000

BOD 10 10 4 4 10 5 5

COD 60 60 15 30 60 40 40

N-org 0.75 0.5 0 0 0 0.75 0.5

N-NH4 2.25 1.5 1 1 2 2.25 1.5

N-NO3 12 8 9 4 4 12 8

Total-P 2 1 0.5 0.5 2* 2 1

Micropollutant

removal efficacy - 0.5 0.3 - 1

*PE<100,000 2 mg/l, for others 1 mg/l

River restoration of the instream morphology and riparian vegetation was

was also taken into account in combination with the tecnological scenarios.

18 GEP Index

Li is the reach length;

(COD)Ti 1 for COD 35 mg/l with 100-DOsat r ≤ 20%

or 15 mg/l if not

0 otherwise;

(N-NH4)Ti 1 for N-NH4 1 mg/l

0 otherwise;

(Total-P)Ti 1 for Total-P 0.5 mg/l.

0 otherwise;

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0 0.5 1 1.5 2 2.5 3

Total-P mg/l

ST

AR

IC

Mi

GEP: Good Ecological Potential

GEP (km) = Li [ (COD)Ti; (N-NH4)Ti; (Total-P)Ti] / 3

Eco

l. M

etr

ic

Environmental gradient

Good Ecological

Potential

10

19 New criteria needed to measure the GEP

LIMeco index is not sensitive enough to detect improvements in these

effluent-dominated streams. Other indexes should be used to assess the

“good ecological potential” of the Lambro-Seveso-Olona system.

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

0 5 10 15 20 25

BOD mg/l

ST

AR

IC

Mii

95°Quantile Regression OLS regression

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0 10 20 30 40 50 60 70 80

COD mg/l

ST

AR

IC

Mi

0

0.1

0.2

0.3

0.4

0.5

0.6

0 1 2 3 4 5 6 7

N-NH4 mg/l

ST

AR

IC

Mi

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0 2 4 6 8 10 12 14

N-NO3 mg/l

ST

AR

IC

Mi

20 New criteria needed to measure the GEP

STAR ICMi (Erba et al., 2009),

which is a biological index broadly

used in Europe to enforce the

WFD, Quantile regression was

used to correlate the

STAR_ICMi 95° percentile

values to the corresponding

chemical ranges

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0 0.5 1 1.5 2 2.5 3

Total-P mg/l

ST

AR

IC

Mi

BOD5 4.0 mg/L COD 15.0 mg/L N-NH4 1.0 mg/L N-NO3 3.0 mg/L TP 0.5 mg/L

Bio

logic

al m

etr

ic

Environmental gradient

Good Ecological

Potential

11

21 Scenario Dir. 271/91

Lambro Settentrionale

0 20 40 60 80 100 120 140

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiume

Olona - Lambro Meridionale

0 5 10 15 20 25 30

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiumeRiver km River km

Northern Lambro Olona- Southern Lambro

GEP: Good Ecological Potential

GEP (km) = Li [(BOD)Ti; (COD)Ti; (N-NH4)Ti; (N-NO3)Ti; (Total-P)Ti] / 5

Li is the reach length;

(BOD)Ti binary variable for BOD 4 mg/l;

(COD)Ti binary variable for COD 15 mg/l;

(N-NH4)Ti binary variable for N-NH4 1 mg/l.

(N-NO3)Ti binary variable for N-NO3 3 mg/l.

(Total-P)Ti binary variable for Total-P 0.5 mg/l.

22 MBR Scenario WWTPs > 50,000 PE


0 20 40 60 80 100 120 140

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiume

Sc271/91

ScMBR


0 10 20 30 40 50

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiume

Sc271/91

ScMBR

River km

Olona Southern Lambro

Northern Lambro

12

23 Scenario MBR 8 WWTPs > 50,000 PE


0 20 40 60 80 100 120 140

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiume

Sc271/91

ScMBR


0 10 20 30 40 50

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiume

Sc271/91

ScMBR

River km

Olona Southern Lambro

Northern Lambro

Only the WWTPs

Influencing at least 80 km

of river stretches

24 Scenario RO (50% blending)

WWTPs > 50,000 PE


0 20 40 60 80 100 120 140

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiume

Sc271/91

ScRO


0 5 10 15 20 25 30 35

GEP

BOD5 (4)

COD (15)

N-NH4 (1000)

N-NO3 (3000)

P tot (500)

km fiume

Sc271/91

ScRO

River km

Northern Lambro

Olona - Southern Lambro

13

25 Hybrid scenarios

Additionally, hybrid scenarios were developed assuming to improve the

conventional treatment only for some plants located in critical positions

along the river stretches and combining different technologies.

MBR LMBR L--OO MBR LMBR L--SS--OOMBR LMBR L--SS--OO

+ GACO3+ GACO3


+ GACO3+ GACO3


+ GACO3+ GACO3

26 Effectiveness

Scenario effectiveness was defined by nine indicators, specifically

designed to quantify the improvement of water quality and of the river

ecological status due to the different alternatives.

Effectiveness

Indexes Description

1. COD river load COD cumulated river load in the river unit

2. Total-N river load Total-N cumulated river load in the river unit

3. Total-P river load Total-P cumulated river load in the river unit

4. DistanceLIMeco Distance from the LIMeco target for the good quality status

5. GEP3 Good Ecological Potential according COD, N-NH4 and Total-P

6. STAR ICMi STAR_ICMi index (Erba et al., 2009)

7. Morphological Index Morphological index after Siligardi et al., 2007

8. Vegetation Index Vegetation Index after Siligardi et al., 2007

9. Micropollutant Index Micropollutants removal efficacy (see Table 2)

14

27 Cost-Evaluation

Sipala S., Mancini G., Vagliasindi F.G.A. 2003. Development of a web-based tool for the calculation of costs of different wastewater treatment and reuse scenarios. Water Science and Technology: Water Supply 3(4), 89–96.

DeCarolis, J., Adham, S., Grounds, J., Pearce, B., Wasserman, J., 2004. Cost Analysis of MBR Systems for Water Reclamation. Proceedings of WEFTEC 2004, New Orleans, 2e6 October.

Coté, P., Masini, M., Mourato, D., 2004. Comparison of membrane options for water reuse and reclamation. Desalination 167, 1-11.

Abegglen C., Siegrist H. 2012: Mikroverunreinigungen aus kommunalem Abwasser. Verfahren zur weitergehenden Elimination auf Kläranlagen. Bundesamt für Umwelt, Bern, Umwelt-Wissen Nr. 1214: 210 S

Finally, a cost of 95,000 euro km-1 and of 85,000 euro km-1 respectively was assumed for the instream morphology and riparian vegetation restoration. A O&M cost of 5,000 euro/km was also assumed for riparian vegetation.

Upgrades were

evaluated as 50%

of the new plant cost

28 Cost-Effectiveness Analysis

The analysis was performed through the mDSS software (Mulino Decision

Support System, Giupponi, 2007).

1. An evaluation matrix was created, normalizing each indicator according to a

certain value function;

2. Indicators are weighted in order to reflect their relative importance in the

computation of the cumulative performance;

3. The cumulative performance, aggregating every single performance on each

specific indicator, is computed by means of a selected decision algorithm.

n

j

ijjiSAW uwa1

Simple Additive Weighting (SAW)

that is the sum of products of the normalized performance

uij in each j-criterion of each i- alternative scenario/measure,

multiplied by the weight given to each j- criterion.

A

Timbro

15


n

j

ijjiSAW uwa1

Water

chemistry

Ecological

Integrity

Morphology

Vegetation

Pollutant loads

COD-Not-Ptot

GEP

STAR ICMi

DistanceLIMeco

Costs

Micropollutants

20%

8%

12%

10%

Investiment O&M

0

1

2

3

4

5

6

7

8

9

10

Dir.271/91 Dir.271/91R PostDen O3/GAC MBR RO

Pollutant loads DistanceLIMeco GEP3

STAR ICMi Instream Morphology Ripatian Vegetation

MicroPollutant Cost_investment Cost_O&M

25% 25%


n

j

ijjiSAW uwa1

Water

chemistry

Ecological

Integrity

Morphology

Vegetation

Pollutant loads

COD-Not-Ptot

GEP

STAR ICMi

DistanceLIMeco

Costs

Micropollutants

20%

8%

12%

10%

Investiment O&M

25% 25%

A

Timbro

A

Timbro

16

31 Cost-Effectiveness Analysis:

final set of scenarios

The restoration of the instream morphology and the riparian vegetation was assumed

in all the reach units with GEP3 > 0.7.

Scenarios Description

Dir.271/91R

upgrade up to the requirements of the Directive 271/91EC

+ instream morphology and riparian vegetation restoration

MBR L-O

secondary MBR in the WWTPs which influence for more tham half of total river length in the Olona and Lambro rivers

MBR L-S-O

secondary MBR in the WWTPs which influence for more tham half

of total river length in the Olona, Seveso and Lambro rivers

MBRR L-O

secondary MBR in the WWTPs which influence for more tham half

of total river length in the Olona and Lambro rivers + instream morphology and riparian vegetation restoration

MBRR L-S-O

secondary MBR in the WWTPs which influence for more tham half of total river length in the Olona, Seveso and Lambro rivers


O3/GAC

ozonation treatment combined with GAC filtration

In all the WWTPs larger than 50,000 PE

O3/GAC-MBR

secondary MBR in the WWTPs which influence for more than half of L-S-O total length and O3/GAC in WWTPs larger than 700,000 PE

O3/GAC-MBRR

secondary MBR in the WWTPs which influence for more than half of L-S-O total length and O3/GAC in WWTPs larger than 700,000 PE


32 Cost-Effectiveness Analysis:

final set of scenarios

Cost-Effectiveness Analysis Scores

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

MBRR L-S-O

MBRR L-O

MBR L-S-O

Dir. 271/91

MBR L-O

O3/GAC-MBRR L-S-O

O3/GAC-MBR L-S-O

O3/GAC

17


• All the scenarios imply a significant increase of the current expenditure

• The increase is far beyond the threshold of 20% that some authors

(Larans, 2006) indicated as a preliminary assessment for disproportionate

costs

0

100

200

300

400

500

600

Sc RO

Sc O3/G

AC

Sc MBR

Sc MBR

L-S-O

Sc O3/G

AC M

BR L-S-O

Sc MBR

L-O

Sc PostDen

Sc Dir 271/91

km

of

river

len

gth

0

30

60

90

120

150

180

% p

lan

ned

in

vestm

ents

GEP (km) total length L-S-O

whole Lombardy Expenditure L-S-O Expenditure

34

Thanks for

the attention

Searching a compromise between ecological quality targets ... · River restoration of the instream...

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